With the convergence of home entertainment technologies, there are a growing number of devices that store many different forms of content, such as music, movies, pictures, TV, videos, games, and so forth. Devices like digital video recorders (DVRs), game consoles, and entertainment-configured computers (e.g., computers running the Windows® XP Media Center operating system from Microsoft Corporation) enable users to record, manage and playback many different forms of content. Even less featured devices, such as set-top boxes, can be designed to record multiple types of content.
As such devices are configured to store more content and offer more functionality, the ability to present the various forms of recorded content in a cohesive, understandable, and user-friendly manner continues to be a challenge. This is particularly true for Graphical User Interface (GUI) based computing devices that are designed to leverage a user's experience for visualizing possible interactions and identification of objects of interest. For instance, use of small icons in a GUI to represent content of respective image files will generally significantly facilitate a user's browsing experience across multiple image files. In this scenario, a small icon may present a visual representation of the content of each image file, so the user is not required to open image files, one by one, to look for an image of interest.
In view of the above, and since a video file comprises visual media, user interaction with video files would be enhanced if a high quality thumbnail that is substantially representative of video content could be presented to a user. Unfortunately, as compared to the relative ease of identifying representative subject matter for a single image file, it is substantially problematic to identify a representative image for a video file. One reason for this is due to inherent characteristics of video data. Video data is time-series based and is typically made up of many image frames—possibly hundreds of thousands of image frames. From such a large number of image frames, it is substantially difficult to determine which particular image frame should be used as a thumbnail to represent the subject matter of the entire video data sequence. Conventional techniques for video thumbnail generation do not overcome this difficulty.
For instance, one existing video thumbnail generating technique uses the very first frame of a video data sequence as a representative thumbnail of the video's content. Unfortunately, the first frame of video data is often a black frame or may include meaningless pre-padding data. A non-representative, black, or low image quality thumbnail may frustrate users, making it difficult for a user to quickly browse through video files (including recorded media content 140). Thus, this conventional technique is unlikely to result in selection of an image frame that will be representative of the video data sequence and substantially limited. Another known technique to generate a thumbnail for video data randomly selects a frame from the video's data sequence for the thumbnail. Such random selection does not take any objective criteria into consideration with respect to the actual content of the video. As a result, the arbitrarily selected frame may present any and often unexpected content including, for example, meaningless, low quality, commercial, noisy, and/or generally unrepresentative subject matter.
Thus, conventional video thumbnail generating techniques typically do not result in a meaningful thumbnail of a video's subject matter. Accordingly, there is a need to apply more objective criteria to locating a video data sequence image frame representative of a video's content. Presentation a thumbnail generated from such an image frame will allow an end-user to more accurately determine if the subject matter of the video is of interest.